聚集还是选择:基于企业动态效率的分解
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F426

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国家社会科学基金重大项目“建设现代化都市圈研究”(21ZDA070);国家自然科学基金项目“城市群网络外部性传导路径与机制研究”(42271189)。


Aggregation or selection:Based on dynamic decomposition of enterprises
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    摘要:

    基于1998—2013年中国工业企业微观数据,考虑企业间互动以及企业动态进入退出的影响,对生产率变动进行分解,将企业间资源配置纳入集聚效应,将企业进入和退出纳入选择效应,更全面分析集聚生产率优势。研究发现,中国城市制造业集聚兼具静态和动态优势。对生产率变动分解发现,中国制造业生产率提升主要来源于集聚效应,集聚效应中企业自身进步贡献度最高,随着集聚水平的提高,资源配置作用越来越重要;选择效应贡献随着集聚水平提高也不断提升,企业退出效应贡献度由2.86%提高到12.82%。实证研究结果表明,制造业集聚对集聚效应中的资源配置影响最大。当前中国制造业集聚处于低水平但不断上升状态,因此资源配置优化和低效率企业在竞争中退出的作用将是未来中国制造业生产率提升的关键。

    Abstract:

    Based on the microscopic data of industrial enterprises in China from 1998 to 2013, considering the interaction between enterprises and the influence of entry and exit of enterprises, this paper decomposes the productivity changes. We take the resource allocation among enterprises into the agglomeration effect, and take the entry and exit into the selection effect to comprehensively analyze the advantages of agglomeration. It is found that China’s urban manufacturing agglomeration has both static and dynamic advantages. The decomposition of productivity changes shows that the productivity improvement of China’s manufacturing industry mainly comes from agglomeration effect, in which the contribution of enterprises’ progress is the highest. With the improvement of agglomeration level, the role of resource allocation becomes more and more important. With the improvement of agglomeration level, the contribution of selection effect is also increasing, and the contribution of enterprise exit effect is increased from 2.86% to 12.82%. The empirical research results show that manufacturing agglomeration has the greatest influence on resource allocation of agglomeration effect. At present, China’s manufacturing agglomeration is at a low level, but it is on the rise. Therefore, the optimization of resource allocation and the exit of inefficient enterprises in the competition will be the key to the improvement of China’s manufacturing productivity in the future.

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姚永玲,王雅蓁.聚集还是选择:基于企业动态效率的分解[J].中国软科学,2024,(4):144-153

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  • 在线发布日期: 2026-07-14
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